© Performance Management Company, 1993 – image used with permission

This is the third in a series of posts about ways in which learning technologies and online learning could improve educational productivity in higher education. The first two posts were:

In response to my first post on this topic, Stephen Downes commented:

Minimally, what we need is a model of educational productivity, not a theory, so we can get a sense of some of the complexities involved. Ideally, we’d get a model suited to the 21st century, not something cooked up by some TQM economists, a model that weighs multiple competing interests, variable outcomes, and competing theories of value.

Well, Stephen, I completely agree – I’ll do my best.

The challenge

In this post I begin by asking a difficult but essential question: how should we measure productivity in higher education? The reason for the question is that we need to be clear about what we are trying to achieve through the use of learning technologies, particularly in terms of outcomes, since productivity is an attempt to improve outcomes at the same or less cost, in this particular instance through the use of technology.

Above all, we need to be careful not to focus on what is easily measurable at the cost of excluding more important outcomes that are more difficult to measure. Also, I am asking you to make a value judgement about what is considered to be the role and function of higher education, and technology’s tole, and there will inevitably be major differences of opinion here, hence the conditional ‘should.’

Lastly, this discussion could easily become very abstract. It’s important not to lose sight of the pragmatics of how learning technologies can be used to bring about changes in university and college teaching, so this should be our starting point. As a result, I’ll start by looking at the possible link between flexible access and productivity.

What are the goals of e-learning?

In my view, unless you are someone whose job depends on the use of learning technologies, technologies and tools are means to an end, not goals in themselves. My hammer in the tool box has no inherent purpose. I may use it to bang in some nails, but even banging nails into wood isn’t a goal in itself.

So I worry when I see institutional plans that set out goals such as 25% of all classes will be hybrid by 2015, or we will have ten fully online masters programs by 2020. It’s like saying I’m going to knock in 10,000 nails over the next five years (or will use a power hammer instead). These may indeed be useful steps in the process of getting somewhere, but we need to be clear about what we are trying to achieve by moving more classes online. One goal of course may be to improve productivity (although it rarely is stated this clearly) – but that still requires a definition of what we are trying to be more productive about.

We shall see that goals in education are like Russian dolls: inside each goal is a set of sub-goals, and within each sub-goal is another set of sub-goals, except that often in education we often start with the smallest sub-goal, then build out to other goals as a post-hoc rationalization for what we are already doing.

So let’s look at some of the educational goals or outputs commonly associated with the use of technology, and then see how these might be measured in some way. In this post, I will focus on just one goal, flexible learning, but will address other goals in later posts.

Increase flexible access to learning

This has been the clearly stated goal of several governments. This goal is in two parts.

1. Using online learning to increase post-secondary participation rates

Thus in Ontario, the government has set the following goals:

  • ensuring space for every qualified Ontario student by creating an additional 60,000 spaces in the system
  • creating the conditions to reach a 70% [post-secondary] attainment rate among Ontario’s adult population.

There are two ‘higher order’ goals behind these more specific goals: equitable access (every qualified Ontario student), and economic development (ensuring that Ontario has a highly qualified work-force that can compete in an increasingly knowledge-based economy). The government could of course attempt to achieve these goals without online learning, merely by building more campus-based institutions. However, the rationale for investing in online learning is that to get to the 70% participation rate, the government has to reach potential students for whom campus-based education is difficult, such as working adults. Indeed, the Ontario government is urging all post-secondary institutions to increase their use of online learning, as a way to increase access.

Thus one simple measurement of this goal is: does the investment in online learning result in a higher participation rate than would have been achieved by an increase in campus-based teaching? Stating the measurement is one thing, though; actually working out how to do the measuring is another. How do we know that if more campuses were built, they wouldn’t reach these students? We are left with more indirect ways of measuring:

  • do we get more older students in online courses? There is fairly strong evidence to date that suggests we do, which suggests online learning is more attractive to lifelong learners. However, we need to also track the demographics of on-campus students, as it seems that these are getting older as well.
  • do we get more students in online courses who are working full-time or even part-time?  Again, there is fairly strong anecdotal evidence that this is the case, but reliable comparative data is in short supply.
  • do we get more students in online courses from other groups previously under-served by campus-based post-secondary education, such as aboriginal students, students with disabilities, new immigrants, etc.? If there is evidence of this kind, I have not seen it, and indeed for some of these groups, online learning may actually be a disadvantage. However, we don’t know, and need to measure this in some way.

My point is that using online learning to increase access to post-secondary education is a feasible, measurable goal. In absolute terms, it would be nice of course to link increased participation rates to increased economic productivity, but a more measurable goal is an actual increase in participation rates that can be directly linked to an increase in online learning activities. Since there is now a good deal of evidence that outcomes are similar between online and campus-based courses, where best practice is followed, then online learning increases productivity by bringing in additional students/learners who would not be able to take campus-based courses. Whether or not this can be done at the same or less cost online is not a factor for this goal, which is a higher participation rate.

I have suggested that the productivity of this approach has been partly measured, but more could be done by institutions through better tracking of student demographics and linking them to mode of delivery (and even more importantly, making such studies publicly available). What we can’t do yet, because no-one has done the study, is to say that online learning has led to an increase of, for instance, 5% per annum in the number of student enrollments over what would have been achieved by increasing campus places, or that a specific sub-group, e.g. new immigrants, that had been mainly excluded is now participating in greater numbers because of online learning. If this is a goal, though (which I think it is), we should be measuring its success.

2. To shorten time to completion of a qualification

The second aspect of measuring the productivity of flexible access is more problematic. This is the rationale that blended/hybrid learning and/or fully online learning is more convenient for existing students, and thus will result in faster completion of qualifications or better grades (I will cover the goal of better grades in another post). This rationale is based on the notion that most so-called full-time students are actually working at least part-time, because of the high cost of tuition. This results in students missing classes, or taking longer to graduate. By providing more flexible access, students can better fit their studies into their busy lives.

Again, there is some evidence to suggest that increased time spent working as well as studying is associated with longer time to completion. We know that in many U.S. universities, students are now taking up to seven years to graduate from a four-year baccalaureate program (put another way, only 35% of students in the USA are completing within four years). This  has been correlated with increases in tuition fees over time. For many years the majority of UBC’s online students (around 85%) were fourth year on-campus undergraduate students taking one or two online courses, either because the face-to-face classes for courses they needed for graduation were full, or because they had dropped one or two courses in previous years, and were trying to make these up to avoid coming back for another year. However, is there any research that analyses the effect of online learning on speed to degree completion of campus-based students? I don’t know of any systematic studies, but this would be a useful indicator of increased productivity due to online learning if such evidence exists.

In these cases we are talking about the impact of fully online courses. Will the same be true for hybrid courses? Will a reduction in class time – but still the need to come on campus at least some of the time – be sufficient to speed up completion rates? Will a more flexible schedule of attendance on campus bring in additional students who are currently unable to attend full-time? Hybrid learning is so new that we just don’t know yet. From a government or institutional perspective, we should be looking at the impact of hybrid learning both in terms of the impact on student enrollments and on time to completion of qualifications.

In terms of both these goals, we should also be examining the relative productivity of alternative approaches to online learning. For instance, would building more campuses be a more effective way to increase enrollments? To do this, though, we would need to know the relative costs (and without doing the study, it appears that online learning would have far lower ‘fixed’ or capital costs per student.) Perhaps more feasibly, how would changes to admission policies such as accepting work experience or prior learning assessment compare with increasing online learning in increasing access without loss of performance?

Lastly, are there other ways to increase access to learning, such as greater use of OERs, MOOCs, remote labs or other technology-based applications? If so, how would we measure their impact on productivity?


It can be seen that there are methodological challenges in trying to assess the impact of online learning on productivity. Nevertheless we don’t have to have perfect answers – we need to know where the balance of evidence is leading. However, at the moment, we don’t have even this – or rather the evidence is scattered across a large range of sources and is not collected together with a view to looking at the issue of productivity.

Indeed, institutions are sitting on much of the data needed to answer many of the questions posed in this post. What is needed is more analysis and communication of the findings that would flow from this analysis. Big data could provide a relatively low cost method of extracting the needed data, but also needed are researchers with the funding and time to do this. A small investment by government in this area could indeed be highly productive and provide useful guidelines for policy.

I believe we can provide reasonably good answers on the impact of online learning on access, at least, and this could show that it has increased the productivity of the system by bringing in students who would otherwise have been excluded.

Coming up next

Not sure – this series of posts is as much an exploration as a map! However, here are some of the topics I’m considering:

1. Can online learning or learning technologies lead to better learning outcomes at the same or less cost than classroom teaching? I will try to define what this might look like, and how this might be measured.

2. Can massive economies of scale be achieved through the use of technology without loss of quality? (One of the issues touched on by Sir John Daniel in his review of Higher Education in the Digital Age – I will try to address this in more detail.) This of course may well overlap or be pre-empted by (1) above, but I’ll probably need at least two posts on this topic anyway.

3. Could technology increase the productivity of faculty – in other words, can technology enable faculty to use their time more productively?

4. Is the quest for improved productivity an appropriate way to look at the use of technology for teaching in higher education? Or does it lead us away from the core benefits of higher education?

5. How could increased collaboration between institutions contribute to increases in productivity? How would this work?

As I said, this is an exploration. I really welcome your suggestions for topics or comments  – even ‘Stop it – it’s boring!’




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